AI-Powered Sewer Systems: Boosting Climate Resilience in City Water Managem

Published Date : 29/10/2025 

The InSchuKa 4.0 project demonstrates how artificial intelligence can enhance the resilience of sewer networks against climate change, managing both heavy rainfall and dry periods effectively. 

Hof / Jena, October 2025 – After three and a half years of intensive research, the joint project InSchuKa 4.0 has come to an end. Its goal: to use artificial intelligence to help sewer networks better respond to heavy rainfall and dry periods—enabling smarter adaptation to climate change.

Climate change is creating growing challenges for municipal water management. Increasingly severe heavy rainfall events are overloading sewer systems, while prolonged dry spells cause pipes to dry out and deteriorate. The research project InSchuKa 4.0 (“Intelligent Control of Sewer Networks”) has tackled this very problem.

For three and a half years, municipal utility partners, technology companies, and research institutions worked together to explore how wastewater systems can be operated safely, efficiently, and in a climate-resilient way in the future. One key focus was integrating operational knowledge into an AI-based case-based reasoning (CBR) system—a method that learns from comparable situations and derives control recommendations for sewer networks.

The project, funded by the German Federal Ministry of Education and Research (BMBF, now BMFTR), was coordinated by Hof University of Applied Sciences. The university’s Institute for Sustainable Water Systems (inwa) led the scientific work and ensured that all partners’ contributions were integrated into a functional overall system.

Smart Valves Instead of Expensive Concrete Basins

At the heart of the project is an innovative concept for digital sewer network management. In Jena, two large stainless-steel gates were installed in the main collector. These can be digitally controlled and will in the future be regulated by an AI-based control system.

The system processes sensor data, hydraulic models, and weather forecasts to decide whether water should be retained within the sewer network or discharged. The aim is to address two opposing but equally urgent challenges of climate change:

Heavy rainfall management: Relieving overloaded sewer systems to prevent flooding.

Dry-weather management: Retaining water in the network to prevent drying and sediment buildup.

“We wanted to show that you can work with existing infrastructure without having to build new retention basins,” says Robert Köllner, Deputy Managing Director of JenaWasser. “Intelligent control makes our sewer network more flexible and resilient against extreme weather.”

Since September 2025, the system has been running in live operation in Jena—a major step from research into real-world application.

Knowledge Transfer: AI Solutions Must Reach Practice

A central goal of InSchuKa 4.0 was not only technical development but also transferring knowledge into municipal practice. The team at Hof University therefore analyzed decision-making processes in utilities and local administrations: What are their expectations of AI-based control systems? What opportunities are seen—and what barriers remain?

A nationwide online survey of 154 professionals from municipalities, engineering firms, and public authorities revealed that intelligent sewer network control is widely recognized as a necessary step toward climate adaptation. At the same time, respondents cited obstacles such as a shortage of skilled staff, limited resources, and the need for transparency in AI-driven decision-making.

Final Event in Jena: Research Meets Practice

To mark the project’s conclusion in October 2025, JenaWasser hosted a closing event. Representatives from municipalities, professional associations, and engineering offices were able not only to hear about the results but also to see them in action. During a live demonstration in the sewer network, the system showed how it activates storage capacity, throttles outflows, and initiates targeted flushing waves.

“With InSchuKa 4.0, we’ve shown that AI in sewer networks is not a vision of the future—it’s already working today,” emphasizes Prof. Günter Müller-Czygan, head of inwa. “The solution is explainable, transferable, and ready for use in other cities.”

From Research to Application: What Comes Next

Even though InSchuKa 4.0 has officially concluded, the collaboration among the project partners continues. The consortium plans to build on the developed concepts and control approaches in new projects—focusing on knowledge transfer, staff training, and further refinement of the AI algorithms.

Hof University will remain an active driving force: from project coordination, a growing network for climate-resilient water management has emerged. 

Frequently Asked Questions (FAQS): 

Q: What is the main goal of the InSchuKa 4.0 project?

A: The main goal of the InSchuKa 4.0 project is to use artificial intelligence to help sewer networks better respond to heavy rainfall and dry periods, enabling smarter adaptation to climate change.

Q: How does the AI system manage heavy rainfall and dry periods?

A: The AI system processes sensor data, hydraulic models, and weather forecasts to decide whether to retain water within the sewer network or discharge it, managing both heavy rainfall and dry periods effectively.

Q: What are the key components of the InSchuKa 4.0 project?

A: The key components include municipal utility partners, technology companies, research institutions, and the integration of operational knowledge into an AI-based case-based reasoning (CBR) system.

Q: What challenges did the project address in municipal water management?

A: The project addressed challenges such as overloading of sewer systems due to heavy rainfall and the deterioration of pipes during prolonged dry spells.

Q: What are the next steps for the InSchuKa 4.0 project?

A: The next steps include knowledge transfer, staff training, and further refinement of the AI algorithms, with continued collaboration among the project partners. 

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